Machine Learning Inspired Smart Agriculture System with Crop Prediction
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Published:2023-01-31
Issue:1
Volume:11
Page:1511-1517
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ISSN:2321-9653
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Container-title:International Journal for Research in Applied Science and Engineering Technology
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language:
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Short-container-title:IJRASET
Author:
Chatterjee Rajdeep,Das Oindrila,Kundu Ridam,Podder Soumik
Abstract
Abstract: This paper presents Machine Learning Inspired Smart Agriculture System with Crop Prediction that will assist farmers in getting Live Data (Temperature, Soil Moisture, level of Nitrogen, Phosphorous and Potassium present in the soil, Alkalinity and Acidity in the soil etc. ) for efficient environment monitoring which will enable them to increase their overall yield and quality of products. The Machine Learning Inspired Smart Agriculture System with Crop Prediction is proposed where Machine Learning Technology is hybridized with different Sensors and a Wi-Fi module that will yield live data feed using online software Localhost and PHPmyadmin. The product being proposed is tested on Live Agriculture Fields giving high accuracy over 98% in data feeds
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
1 articles.
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1. Crop Recommendation and Yield prediction Using Machine Learning based Approaches;2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST);2024-04-09